A vehicle crash sensing system detects and discriminates severe crash events which require deployment of an airbag, such as those listed in Table 1, from minor crash incidents which do not, such as those listed in Table 2.
TABLE 1 ______________________________________ Type of Collision Speed Range (mph) ______________________________________ Full frontal to barrier (F/B) 12-30 30.degree. right angle to barrier (R/B) 20-30 30.degree. left angle to barrier (L/B) 20-30 On-center pole (C/P) 15-30 Full frontal to rear of parked car 60 ______________________________________
TABLE 2 ______________________________________ Event or Incident Upper Speed (mph) ______________________________________ Undercarriage Hit (U/H) 20 Car to Deer (D/H) 50 Square block road (S/B) 40 Chatter bumps 60 Hood slams N/A Door Slams N/A Hammer blows (5-8 lbs.) N/A ______________________________________
Discrimination is accomplished by means of a vehicle-mounted accelerometer and an associated signal processing algorithm contained within a microprocessor. Since the total available time for deploying an airbag to effectively restrain occupants in a severe crash event is very short, the ability to quickly and reliably determine the severity of a collision is paramount. Equally important is the system's immunity to inadvertent deployment during minor crash incidents.
Many prior art airbag deployment algorithms have been developed which utilize one or more quantities for measuring the severity of a collision. These "quantities" or "parameters" have included vehicle velocity change, energy, power, power-rate, jerk, predicted occupant/interior contact velocity, predicted occupant movement, energy of a vehicle deceleration signal, and oscillation measure of the vehicle deceleration signal. The value of these quantities are generally calculated as a function of successively sampled accelerometer data. Based upon test data obtained from the accelerometer during a representative set of minor crash incidents, one or more boundary thresholds are set. Airbag deployment is initiated whenever the values of some or all of these quantities exceed their respective boundary thresholds.
For example, in U.S. Pat. No. 5,339,242, issued Aug. 16, 1994, to Reid et al., a crash sensing system is disclosed in which time-dependent jerk and velocity change data represent two crash severity conditions which are continually consulted following the onset of a crash event in order to determine whether vehicle safety devices should be actuated.
As illustrated in FIG. 1, many minor crash incidents including, 20 mph undercarriage hits (U/H) 10, 50 mph simulated deer hits (D/H) 12 and square block rough road incidents (S/B) 14 are characterized by a rapid decrease in vehicle velocity over a relatively short duration, which thereafter quickly levels off. On the other hand, FIG. 2 illustrates that vehicle velocity changes of severe crash events including, 30 mph frontal barrier (F/B) 16, 30 mph left angle to barrier (L/B) 18, 30 mph right angle to barrier (R/B) 20, 30 mph on center high pole (C/P) 22 and 13 mph increase slowly following the onset of the crash event but shortly thereafter increases monotonically.
As can be realized from the above, if vehicle velocity change (calculated as a function of acceleration) is used as a crash severity parameter, accelerometer data generated during the initial stages of a crash event (e.g., up to the first 25 msec.) can be misleading. A nondeployment type minor crash incidem may initially produce a higher deceleration signal value (and corresponding higher velocity change value) than a deployment type severe crash event. Lowering threshold levels to increase deployment sensitivity (i.e., reduce deploymere time) may result in the initially higher velocity change values of the minor crash incidents exceeding the boundary threshold levels, inadvertently deploying the airbag.
Use of crash severity parameters other than vehicle velocity change characterized by similar severe-versus-minor crash event signal traces as those of the vehicle velocity change parameter will similarly be susceptible to the potentially misleading acceleration data generated during the initial stages of the crash event.